Data can also be referred to as raw facts, it’s meant to be processed into meaningful information that can be used in decision making by organizations. Data metamorphosis into information after it has been passed through several data analytical processes.
Examples of data: names of students in a class, results of an experiment, GDP of different countries in Europe, heights of students, BMI of patients, tweets, list of students in a faculty, videos uploaded on YouTube, audio files uploaded on sportify, etc.
Data is everywhere, data is being generated in every sector but there’s a difference in how data is being harnessed into information in different sectors.
For example, music/video streaming platforms makes use of the data generated on how you interact with their platform e.g music genre and artists you listen to, most played songs, location, etc to come up with song and playlist recommendations for you.
Search engines use search history, location data etc to come up with search results and adverts.
E-commerce businesses use purchase history data, search
history, customer preferences to come up with personalized product recommendations and advertisements for their customers.
E-commerce businesses use purchase history data, search
history, customer preferences to come up with personalized product recommendations and advertisements for their customers.
Data can be gotten from surveys/questionnaires, social-media, organizations, government, sensors/machines/instruments.
In my next post, I’ll briefly address each of these with suitable examples.
I’m sure now, when you hear the word data, you can have a mental picture of what’s being referred to🤝🤝🤝 and you also know that it’s used in different sectors.
I’m sure now, when you hear the word data, you can have a mental picture of what’s being referred to🤝🤝🤝 and you also know that it’s used in different sectors.
So, that’s all for now and we meet next week🤝🤝🤝
Happy new month❤️❤️
Happy new month❤️❤️
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